Online Public Access Catalogue (OPAC)
Library,Documentation and Information Science Division

“A research journal serves that narrow

borderland which separates the known from the unknown”

-P.C.Mahalanobis


In silico identification of toxins and their effect on host pathways: (Record no. 428024)

MARC details
000 -LEADER
fixed length control field 02638nam a2200301 4500
001 - CONTROL NUMBER
control field th490
003 - CONTROL NUMBER IDENTIFIER
control field ISI Library, Kolkata
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240923125845.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210118b ||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency ISI Library
Language of cataloging English
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 23rd.
Classification number 571.95
Item number R595
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sen, Rishika
Relator term author
245 10 - TITLE STATEMENT
Title In silico identification of toxins and their effect on host pathways:
Remainder of title feature extraction classification and pathway prediction/
Statement of responsibility, etc Rishika Sen
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Kolkata:
Name of publisher, distributor, etc Indian Statistical Institute,
Date of publication, distribution, etc 2021
300 ## - PHYSICAL DESCRIPTION
Extent 272 pages,
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Ph.D.) - Indian Statistical Institute, 2021
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliography
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction and Scope of the Thesis -- A Review on Host–Pathogen Interactions: Classification and Prediction -- PyPredT6: An Ensemble Learning-based System for Identification of Type VI Effector Proteins -- Cluster Quality-based Non-Reductional (CQNR) Oversampling Technique and Effector Protein Predictor Based on 3D Structure (EPP3D) of Proteins -- DeepT7: A Deep Neural Network System for Identification of Type VII Effector Proteins -- DeepT7: A Deep Neural Network System for Identification of Type VII Effector Proteins -- Boolean Logic-based Network Robustness Analyzer (BNRA) and Its Application<br/>to a System of Host-Pathogen Interactions -- Conclusions and Scope for Future Research
508 ## - CREATION/PRODUCTION CREDITS NOTE
Creation/production credits note Guided by Prof. Rajat K. De
520 ## - SUMMARY, ETC.
Summary, etc Identification of toxins, which are either proteins or small molecules, from pathogens is of paramount importance due to their crucial role as first-line invaders infiltrating a host, often leading to infection of the host. These toxins can affect specific proteins, like enzymes that catalyze metabolic pathways, affect metabolites that form the basis of metabolic reactions, and prevent the progression of those pathways, or more generally they may affect the regular functioning of other proteins in signaling pathways in the host. In this regard, the thesis addresses the problem of identification of toxins, and the effect of perturbations by toxins on the host pathways based on three tasks: feature extraction, classification and pathway prediction. The thesis starts with in silico identification of such toxins in pathogens. This is followed by the analysis of the effect of toxins on various metabolic and signaling pathways of the host.
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Physiology and related subjects
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Disease
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Toxicology
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Toxins
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pathway prediction
856 ## - ELECTRONIC LOCATION AND ACCESS
Link text Full text
Uniform Resource Identifier <a href="http://dspace.isical.ac.in:8080/jspui/handle/10263/7117">http://dspace.isical.ac.in:8080/jspui/handle/10263/7117</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type THESIS
Holdings
Lost status Not for loan Home library Current library Date acquired Full call number Accession Number Koha item type Public note
    ISI Library, Kolkata ISI Library, Kolkata 18/01/2021 571.95 R595 TH490 THESIS E-Thesis
Library, Documentation and Information Science Division, Indian Statistical Institute, 203 B T Road, Kolkata 700108, INDIA
Phone no. 91-33-2575 2100, Fax no. 91-33-2578 1412, ksatpathy@isical.ac.in